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Okay, got it meanwhile. There are probably different ways to do this but this one works fine. Apart from access to your Spatialite database via Python's sqlite3 module and the Spatialite extension, you'll need the geojson module (simply installable with pip). Connect to your database as usual: import sqlite3 import geojson # open a Spatialite database ...


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Your database is not really a SpatiaLite database but a SQLite database which contains geometries which are encoded according to FDO specification. Something about FDO can be read from http://trac.osgeo.org/fdo/wiki/FDORfc16. Some other software, like TatukGIS, are also creating SQLite databases with FDO geometries. Spatialite can read FDO geometries ...


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I have by chance this morning discovered a secondary answer to this question which I've not seen mentioned anywhere, and which seems worth a full description. The CSV file is loaded into QGIS in the normal way (using the button for doing this). Then this can be saved as (right click the layer entry and 'Save as...') an ESRI Shapefile. This produces a couple ...


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Accordingly to Spatialite coockbook you must register your VIEW into the views_geometry_columns, so to make it become a real Spatial View, i.e.: INSERT INTO views_geometry_columns (view_name, view_geometry, view_rowid, f_table_name, f_geometry_column) VALUES ('buffer500m', 'geometry', 'ROWID', 'point', 'geom');


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Okay, meanwhile I found out how this can be achieved. I don't know if this is the most efficient way but for my tables which are not huge it works fast enough. The idea is that geopandas stores geometries as shapely geometry objects in each row of the geometry column of a GeoDataFrame (which is in fact just a GeoSeries) so that most of shapely's methods can ...


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though this question has been out there awhile, i wanted to post what seems to have worked for me (which sounded almost identical to the OP question). Following the bug report from http://hub.qgis.org/issues/8923 to https://groups.google.com/forum/#!topic/spatialite-users/FOq1DPRDkJw, i tried the following (python implementation): ...


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If you're working with spatialite, here's how to do what you want: The SQL format is INSERT INTO ... SELECT FROM ... So, suppose you have a permanent spatial table "trees" with columns attrib1, attrib2, attrib3. Now one of the field guys brings a new shapefile "new_trees" with equivalent fields col_x, col_y, col_z. You would import the new shapefile into ...


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Maybe you can start to have a look at Vespucci. It is an opensource OSM editor for Android devices who can display map tiles mainly from OSM based sources, but it should be possible to display any other non-tiled map imagery, I assume. And inside Vespucci you can display the current GPS position, but I am not aware whether this is using any google service ...


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It works quite fast for me. I used http://download.geofabrik.de/europe-latest.osm.pbf as sample data and converted the points layer into Spatialite database as ogr2ogr -f sqlite -dsco spatialite=yes europe_points.sqlite europe-latest.osm.pbf points -progress -lco spatial_index=no Then I created CSV file as ogr2ogr -f "CSV" commandtmp.csv ...


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You can use Foreign Data Wrappers, as of Postgres 9.2 (I think), from within Postgres to register a connection to another data source, either a Postgres server on another machine, or a completely separate data source. CREATE EXTENSION postgres_fdw; CREATE SERVER foreign_spatial_lite FOREIGN DATA WRAPPER postgres_fdw OPTIONS (dbname 'some_dbname', ...


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You can only connected to one (and only one) database in the DB Manager to run the SQL window. So this is not possibly. Either your way of cloning the data, or making the join inside QGIS in the Properties > Joins tab of one of the layers.



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